Although a large number of datasets gathered as Linked Open Data (LOD) is better for data sharing and re-using, the datasets themselves become more difficult to understand. Since each dataset has its own data structure, we need to understand datasets individually. In addition, since the entities in datasets are interconnected, we need to understand the interconnections between datasets. In othe...

The project objective was to determine the CLA content of three muscles (Longissimus lumborum, LD; Semimembranosus, SM; Triceps brachii, TB), in both raw and cooked states, in cattle finished on pasture or with grain supplements. Cattle were randomly assigned to one of four finishing regimens; pasture (n=11), pasture with grain supplement (n=11), pasture with grain supplement containing soyoil ...

The occurrence of discoloured water at the tap is one of the most frequent reasons for customers to complain. Water discolouration arises from the resuspension of loose deposits (LD) that accumulate in drinking water pipes, due to velocity increase. Because of its typical brownish/reddish colour, discoloured water is traditionally perceived as a consequence of cast-iron pipes corrosion, even in...

In this study, a modified salting-out-assisted liquid-liquid extraction (SALLE) combined with low density dispersive microextraction (LD-DLLME) has been developed for quantitative determination of multiclass pesticide residues (atrazine, diazinon, ametryn, terbutryn, chlorpyrifos, dimethametryn, 4,4'-dichlorodiphenyldichloroethylene (4,4'-DDE), 4,4'-dichlorodiphenyldichloroethane (4,4'-DDD) and...

The problem of optimal fixed lag smoothing of a diffusion process, xt is to estimate xt−τ for t > τ , given the output of a nonlinear noisy sensor up to time t. The nonlinear filtering-smoothing problem is to estimate both xt and xt−τ . The optimal estimators are the conditional expectations of the processes, given the measurements. We derive evolution equations for both the normalized and unno...

(i) βt(xt → xt|Xi = x) = E[Yit|Xi = x′]− E[Yit|Xi = x], (ii) FYiτ |Xi(.|x) = FYiτ |Xi(.|x) Proof (i) follows by the correlated-random-effects assumption and h(x) = h(x′) βt(xt → xt|Xi = x′) = ∫ (ξt(x ′ t, a, u)− ξt(x, a, u))FAi,Uit|Xi(a, u|x ′) = E[Yit|Xi = xt]− ∫ ξt(xt, a, u))dFAi,Uit|Xi(a, u|h(x)) = E[Yit|Xi = x]− E[Yit|Xi = x]. ∗University of California, Davis, One Shields Ave, Davis CA 9561...

EXt = μ Cov(Xt, Xt−k) = γk (lag-k autocovariance). The lag zero autocovariance γ0 is just the variance of the time series. γk’s are of central importance in time series analysis as they characterize the serial dependence over observations (i.e. over time). We usually do not have iid data in time series contexts. A white noise series is stationary. A white noise (WN) series is defined as an unco...